Problem with the code of VAE in main.py

[Yuxing0926]

Traceback (most recent call last):
File "/Users/mayuxing/Downloads/FTCP-master 2/main.py", line 55, in
VAE.fit([X_train, y_train],
File "/Users/mayuxing/opt/anaconda3/lib/python3.9/site-packages/keras/utils/traceback_utils.py", line 67, in error_handler
raise e.with_traceback(filtered_tb) from None
File "/var/folders/pr/t7phtfp9055f_v4lkb49g73c0000gn/T/autograph_generated_file32azsqjs.py", line 15, in tf__train_function
retval = ag_.converted_call(ag__.ld(step_function), (ag__.ld(self), ag__.ld(iterator)), None, fscope)
TypeError: in user code:

File "/Users/mayuxing/opt/anaconda3/lib/python3.9/site-packages/keras/engine/training.py", line 1051, in train_function  *
    return step_function(self, iterator)
File "/Users/mayuxing/opt/anaconda3/lib/python3.9/site-packages/keras/engine/training.py", line 1040, in step_function  **
    outputs = model.distribute_strategy.run(run_step, args=(data,))
File "/Users/mayuxing/opt/anaconda3/lib/python3.9/site-packages/keras/engine/training.py", line 1030, in run_step  **
    outputs = model.train_step(data)
File "/Users/mayuxing/opt/anaconda3/lib/python3.9/site-packages/keras/engine/training.py", line 890, in train_step
    loss = self.compute_loss(x, y, y_pred, sample_weight)
File "/Users/mayuxing/opt/anaconda3/lib/python3.9/site-packages/keras/engine/training.py", line 948, in compute_loss
    return self.compiled_loss(
File "/Users/mayuxing/opt/anaconda3/lib/python3.9/site-packages/keras/engine/compile_utils.py", line 239, in __call__
    self._loss_metric.update_state(
File "/Users/mayuxing/opt/anaconda3/lib/python3.9/site-packages/keras/utils/metrics_utils.py", line 70, in decorated
    update_op = update_state_fn(*args, **kwargs)
File "/Users/mayuxing/opt/anaconda3/lib/python3.9/site-packages/keras/metrics/base_metric.py", line 140, in update_state_fn
    return ag_update_state(*args, **kwargs)
File "/Users/mayuxing/opt/anaconda3/lib/python3.9/site-packages/keras/metrics/base_metric.py", line 449, in update_state  **
    sample_weight = tf.__internal__.ops.broadcast_weights(
File "/Users/mayuxing/opt/anaconda3/lib/python3.9/site-packages/keras/engine/keras_tensor.py", line 254, in __array__
    raise TypeError(

TypeError: You are passing KerasTensor(type_spec=TensorSpec(shape=(), dtype=tf.float32, name=None), name='Placeholder:0', description="created by layer 'tf.cast_2'"), an intermediate Keras symbolic input/output, to a TF API that does not allow registering custom dispatchers, such as `tf.cond`, `tf.function`, gradient tapes, or `tf.map_fn`. Keras Functional model construction only supports TF API calls that *do* support dispatching, such as `tf.math.add` or `tf.reshape`. Other APIs cannot be called directly on symbolic Kerasinputs/outputs. You can work around this limitation by putting the operation in a custom Keras layer `call` and calling that layer on this symbolic input/output.

I dont know how to debug this. Look forward to you answer. :)

[sgbaird]

@469900626 maybe give the notebook mentioned here a try (make sure it runs to completion), and then swap the existing data with your data?

Also, a reproducer would probably help the devs to debug this.

[Yuxing0926]

Thanks for your reply! :)